Statistical optimization of culture conditions for enhanced xylanase production by bacillus species using response surface methodology

Introduction

Xylanases (endo-1,4-β-xylanases, EC 3.2.1.8) cleave the β-1,4-glycosidic bonds in the xylan backbone, the second most abundant polysaccharide in plant cell walls after cellulose [1] . Industrial interest in these enzymes spans pulp bleaching, animal feed supplementation, bread-making, biofuel pretreatment, and waste valorization [2] . Bacterial xylanases, particularly those from Bacillus genera, attract attention because of their thermal stability, broad pH tolerance, and ease of large-scale cultivation [3] . Microbial enzyme yield depends heavily on culture parameters. Temperature, pH, carbon source type and concentration, nitrogen source, inoculum size, and agitation speed all interact in ways that One-Factor-at-a-Time (OFAT) approaches struggle to capture [4] . Traditional OFAT methods test each variable independently while holding others constant, missing synergistic or antagonistic interactions between factors [5] . Response surface methodology addresses this limitation by fitting polynomial models to systematically designed experiments, mapping the response landscape, and identifying optimal operating points with far fewer runs than full factorial designs would require [6] . Among RSM designs, the Central Composite Design (CCD) has become a standard choice for enzyme optimization research. CCD combines factorial, axial, and center points to estimate linear, quadratic, and interaction effects within a single experimental framework [7] . Paired with Plackett-Burman screening to first narrow down the most influential variables, CCD enables efficient two-stage optimization [8] . Several groups have applied this strategy to xylanase production by Bacillus subtilis [9] , Bacillus pumilus [10] , and Bacillus halodurans [11] , but reported optima vary widely depending on strain origin and substrate availability. Canadian forest ecosystems harbor a rich pool of lignocellulose-degrading bacteria that remain largely uncharacterized for enzyme potential [12] . Isolating strains adapted to local substrates may yield xylanases with properties suited to regional industrial needs, particularly in the pulp and paper sector. This research aimed to isolate a xylanase-producing Bacillus species from Canadian hardwood decomposition sites, screen culture variables for significance using a Plackett-Burman design, and optimize the three most important factors through CCD-based RSM.

Material and Methods

Material

Decomposing hardwood samples (maple and birch) were collected from forested areas surrounding the Toronto Metropolitan University campus between May and July 2023. Beechwood xylan, birchwood xylan, and all culture media components were sourced from established laboratory suppliers. Nutrient agar, Luria-Bertani broth, and mineral salt medium were prepared according to standard formulations. Congo red dye was used for xylanolytic zone detection. DNA extraction kits and 16S rRNA universal primers (27F/1492R) were obtained for molecular identification. All chemicals were of analytical grade or higher. The dinitrosalicylic acid (DNS) reagent for reducing sugar estimation was prepared fresh before each assay batch [13] .

Methods

Bacillus isolates were obtained by serial dilution plating of decomposed wood suspensions onto xylan-mineral salt agar followed by incubation at 37°C for 48 hours. Colonies showing clear zones on Congo red-stained plates were selected and purified. The highest-producing isolate (designated BX-17) was identified as Bacillus sp. based on morphological, biochemical, and 16S rRNA sequence analysis (99.2% similarity to Bacillus subtilis). Xylanase production was carried out in 250 mL Erlenmeyer flasks containing 100 mL mineral salt medium supplemented with beechwood xylan as the sole carbon source, incubated in an orbital shaker. Enzyme activity was determined by the DNS method, measuring reducing sugars released from 1% xylan substrate at 50°C for 10 minutes [14] . One unit of xylanase activity was defined as the amount releasing one micromole of xylose equivalents per minute. A Plackett-Burman design with 12 runs screened six variables: temperature (30-45°C), pH (5.0-9.0), substrate concentration (0.5-3.0%), inoculum size (1-5%), agitation speed (100-200 rpm), and incubation time (24-96 hours). The three significant factors (temperature, pH, substrate concentration) were then optimized using a 2³ CCD with five center points, yielding 20 experimental runs. Design-Expert software version 13.0 was used for model fitting, ANOVA, and numerical optimization [15] .

Reagents and chemicals

Beechwood xylan (purity ≥90%) served as the primary substrate. Peptone, yeast extract, magnesium sulfate heptahydrate, dipotassium hydrogen phosphate, and ammonium sulfate formed the basal medium components. DNS reagent was prepared by dissolving 3,5-dinitrosalicylic acid in sodium hydroxide solution with the addition of sodium potassium tartrate and phenol [13] . D-xylose standards (0.2-2.0 mg/mL) were prepared for calibration curves. Sodium acetate buffer (50 mM, pH 5.0) was used for enzyme-substrate reactions. Bradford reagent was used for protein quantification. All glassware was autoclaved at 121°C for 15 minutes before use.

Quality control

Each experimental run in the CCD was performed in triplicate, and mean values were used for model fitting. Dxylose standard curves were generated fresh for each analytical session, with acceptable linearity (R² > 0.995). Blank reactions without enzyme were run alongside all assays to correct for non-enzymatic sugar release. The DNS assay coefficient of variation across replicate measurements was kept below 5%. Center point replication (five runs) provided an internal estimate of pure error for ANOVA lack-of-fit testing. Positive control assays using a commercial xylanase preparation confirmed assay system performance within expected ranges. The quadratic model was highly significant (F = 29.74, p<0.0001) with a non-significant lack of fit (p = 0.214), indicating good predictive capacity (Table 2). Temperature exerted the strongest individual effect (31.2% contribution), followed by pH (24.7%) and substrate concentration (18.3%). The temperature-pH interaction was the only significant two-way interaction (p = 0.003).

Results

Discussion

The 2.4-fold improvement in xylanase yield through RSM optimization aligns with enhancements reported for related Bacillus strains. Sanghi et al. [9] achieved a 2.1-fold increase for B. subtilis ASH using Box-Behnken design, while Nagar et al. [10] reported 2.8-fold improvement for B. pumilus SV-85S with CCD. The optimum temperature of 37°C observed here falls within the typical mesophilic range for Bacillus xylanases, though thermophilic strains can prefer temperatures above 50°C [16] . The neutral pH optimum (7.0) differs from the slightly alkaline preference (pH 8.0-9.0) reported for alkaliphilic Bacillus isolates from soda lakes [11] , reflecting the origin of our strain from forest floor environments with near-neutral soil pH.

The dominant effect of temperature on xylanase yield is consistent with the known sensitivity of Bacillus protein expression machinery to thermal regulation [17] . The significant temperature-pH interaction (p = 0.003) suggests that enzyme stability and cellular metabolism respond jointly to these parameters, a relationship that OFAT approaches would miss entirely. Substrate concentration showed a clear optimum at 1.8%, with higher levels likely causing catabolite repression or viscosity-related mass transfer limitations in shake flask cultures [18] .

Limitations

This research was limited to shake-flask scale, and behavior in bioreactor systems may differ because of altered mixing and oxygen transfer dynamics.

Conclusion

This research demonstrated that a two-stage statistical strategy combining Plackett-Burman screening with central composite design-based RSM effectively optimized xylanase production by Bacillus sp. BX-17 isolated from Canadian hardwood ecosystems. Temperature, pH, and substrate concentration were identified as the three dominant factors, with their combined effects well-captured by a quadratic model (R² = 0.964). Optimized conditions of 37°C, pH 7.0, and 1.8% beechwood xylan concentration yielded 183.7 U/mL, a 2.4-fold increase over baseline. The enzyme showed favorable stability across industrially relevant pH and temperature ranges. These findings highlight the value of local microbial biodiversity as a source of industrially useful enzymes and confirm RSM as an efficient optimization framework for microbial enzyme production.

Acknowledgement

Acknowledgements Funding SourcesThis research received support from the Toronto Metropolitan University Faculty of Science internal research fund. Institutional supportThe authors acknowledge the Department of Microbiology and Biotechnology for providing fermentation and analytical laboratory access.

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